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roberta-base-csqa_pfeiffer
AdapterHub/roberta-base-csqa_pfeiffer
roberta-base-csqa_pfeiffer is a machine learning model from AdapterHub. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for adapter-transformers. The card lists the license as apache-2.0.
Pfeiffer Adapter trained on Commonsense QA.
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At a glance
- Library
- adapter-transformers
- License
- apache-2.0
- Access
- Public
- Created
- May 5, 2024
- Updated
- May 5, 2024
- SHA
- d4f85506
Datasets
Model card
From the Hugging Face model README
Adapter roberta-base-csqa_pfeiffer for roberta-base
Pfeiffer Adapter trained on Commonsense QA.
This adapter was created for usage with the Adapters library.
Usage
First, install adapters:
pip install -U adapters
Now, the adapter can be loaded and activated like this:
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("roberta-base")
adapter_name = model.load_adapter("AdapterHub/roberta-base-csqa_pfeiffer")
model.set_active_adapters(adapter_name)
Architecture & Training
- Adapter architecture: pfeiffer
- Prediction head: None
- Dataset: Commonsense QA
Author Information
- Author name(s): Jonas Pfeiffer
- Author email: jonas@pfeiffer.ai
- Author links: Website, GitHub, Twitter
Citation
@article{Pfeiffer2020AdapterFusion,
author = {Pfeiffer, Jonas and Kamath, Aishwarya and R{\"{u}}ckl{\'{e}}, Andreas and Cho, Kyunghyun and Gurevych, Iryna},
journal = {arXiv preprint},
title = {{AdapterFusion}: Non-Destructive Task Composition for Transfer Learning},
url = {https://arxiv.org/pdf/2005.00247.pdf},
year = {2020}
}
This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/roberta-base-csqa_pfeiffer.yaml.
- Library
- adapter-transformers
- License
- apache-2.0
- Created
- May 5, 2024
- Updated
- May 5, 2024